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Edge Ai Machine Learning Jobs in Minnesota (NOW HIRING)

Machine Learning Engineer

Minneapolis, MN ยท On-site

$85K - $125K/yr

We seek to advance AI, CV, and other related fields through research and development and ... Machine learning experience using visual data * Understanding of a variety of machine learning ...

We seek to advance AI, CV, and other related fields through research and development and ... Machine learning experience using visual data * Understanding of a variety of machine learning ...

Machine Learning Engineer

Minneapolis, MN ยท On-site

$85K - $125K/yr

We seek to advance AI, CV, and other related fields through research and development and ... Machine learning experience using visual data * Understanding of a variety of machine learning ...

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Edge Ai Machine Learning information

What is an Edge AI Machine Learning job?

An Edge AI Machine Learning job involves developing and deploying machine learning models directly on edge devices, such as IoT sensors, mobile devices, and embedded systems. This role requires expertise in optimizing AI models for low-power, low-latency environments while ensuring real-time processing. Professionals in this field work with frameworks like TensorFlow Lite, ONNX, and OpenVINO to implement AI solutions efficiently. They must also handle challenges like model compression, hardware acceleration, and data privacy.

What are some typical challenges faced in an Edge AI Machine Learning role, and how can I prepare for them?

One of the most common challenges in Edge AI Machine Learning is optimizing models to run efficiently on hardware with limited resources, while maintaining acceptable accuracy and speed. You may encounter constraints related to memory, processing power, and connectivity, which require creative engineering and a deep understanding of both machine learning and embedded systems. Collaborating closely with hardware engineers, data scientists, and software developers is typical, as solutions often span multiple technical disciplines. To prepare, staying current with advancements in model compression, quantization, and edge deployment technologies will help you tackle these challenges with confidence.

What are the key skills and qualifications needed to thrive in the Edge Ai Machine Learning position, and why are they important?

To thrive as an Edge AI Machine Learning professional, you need a strong background in machine learning algorithms, embedded systems, and proficiency with programming languages such as Python or C++. Familiarity with edge computing platforms (like NVIDIA Jetson, Google Coral), frameworks (TensorFlow Lite, ONNX), and certifications in AI or ML can greatly enhance your qualifications. Strong problem-solving abilities, collaboration, and effective communication skills are important for adapting solutions to diverse environments and working cross-functionally. These abilities enable the successful deployment of efficient and robust AI models directly on devices, meeting the unique challenges of real-time, resource-constrained settings.

What are the most commonly searched types of Edge Ai Machine Learning jobs in Minnesota? The most popular types of Edge Ai Machine Learning jobs in Minnesota are:
What are popular job titles related to Edge Ai Machine Learning jobs in Minnesota? For Edge Ai Machine Learning jobs in Minnesota, the most frequently searched job titles are:
What cities in Minnesota are hiring for Edge Ai Machine Learning jobs? Cities in Minnesota with the most Edge Ai Machine Learning job openings:
Infographic showing various Edge Ai Machine Learning job openings in Minnesota as of July 2026, with employment types broken down into 79% Full Time, 9% Part Time, and 12% Contract. Highlights an 94% In-person, and 6% Remote job distribution.
Data Science, AI & Analytics Lead

Data Science, AI & Analytics Lead

FORWARD EDGE AI, INC

Saint Paul, MN โ€ข On-site

Contractor

Posted 25 days ago


Job description

Data Science, AI & Analytics Lead
Location: Fort Snelling, MN
Work Arrangement: Hybrid (Must reside within 50 miles of Fort Snelling, MN)
Clearance: Active Secret Clearance Required
Employment Type: Full-Time
Position Overview
Forward Edge-AI is seeking a Data Science, AI & Analytics Lead to support the U.S. Army Reserve CIO/G-6. This position will lead enterprise data analytics, artificial intelligence, machine learning, visualization, and data governance initiatives that enable data-driven decision-making, operational readiness, and digital transformation across the Army Reserve enterprise.
The ideal candidate will provide technical leadership for advanced analytics programs, develop executive-level dashboards and reporting solutions, guide AI/ML implementation efforts, and ensure compliance with enterprise data governance and quality standards. This role requires the ability to communicate complex analytical findings to senior military and civilian leadership and translate data into actionable business insights.
Work Location Requirement
This is a hybrid position. Candidates must reside within 50 miles of Fort Snelling, MN and be available to work on-site as required to support meetings, stakeholder engagements, workshops, and Government-directed activities. Candidates must be able to obtain and maintain installation access.
Key Responsibilities
  • Lead the development and implementation of AI/ML models, predictive analytics, and advanced data science solutions
  • Design and deliver executive dashboards, reports, scorecards, and visualizations using Power BI and other approved analytics platforms
  • Analyze structured and unstructured data to support operational readiness, strategic planning, and executive decision-making
  • Oversee enterprise data integration, ETL processes, API development, and data engineering activities
  • Establish and maintain data governance frameworks, metadata standards, and data quality controls
  • Identify authoritative data sources and ensure compliance with Army and DoD data strategies
  • Evaluate emerging technologies and recommend innovative solutions that support enterprise modernization initiatives
  • Brief senior military and civilian leadership on analytical findings, recommendations, and program performance
  • Collaborate with stakeholders, data engineers, analysts, and technical teams to deliver mission-focused solutions
  • Support Agile, DevSecOps, and modern data platform practices
  • Provide technical leadership and mentorship to analytics and data teams

Required Qualifications
  • Bachelor's or Master's degree in Data Science, Computer Science, Mathematics, or a related field
  • Minimum of five (5) years of experience in data science, analytics, AI/ML, business intelligence, or related disciplines
  • Experience developing predictive models, machine learning solutions, and advanced analytics products
  • Proficiency with Python, SQL, Power BI, Azure Machine Learning, Databricks, or similar analytics platforms
  • Experience with data integration, ETL development, and enterprise data management
  • Strong understanding of data governance, data quality, metadata management, and data stewardship
  • Experience supporting federal agencies, Department of Defense organizations, or large enterprise environments
  • Active Secret Security Clearance
  • U.S. Citizenship required
  • Ability to communicate complex technical concepts to executive and non-technical audiences

Preferred Qualifications
  • Experience supporting Army, DoD, or federal data and analytics programs
  • Experience with Army Vantage, Advana, Azure cloud environments, or similar enterprise platforms
  • Microsoft, Azure, AI/ML, Data Analytics, Agile, or Project Management certifications
  • Experience leading cross-functional technical teams
  • Experience briefing General Officer, Senior Executive Service, or executive-level stakeholders

Why Forward Edge-AI
At Forward Edge-AI, you will work alongside mission-focused professionals delivering cutting-edge AI, analytics, and data solutions that directly support national defense objectives. Join a team committed to innovation, collaboration, and advancing the future of data-driven decision-making across the Department of Defense.